A Guide to Developing Algorithmic Trading Strategies

 

A Guide to Developing Algorithmic Trading Strategies - Trading is an excellent opportunity for one to make money. In fact, since the whole idea of day trading was introduced to ordinary people, the fact is that many people have quit their jobs to become day traders. In fact, I recently held a conversation with a young Kenyan guy who is making a fortune as a day trader. In the past, this was not possible because the software to execute the trades was not available. In addition, the information was not available to retail traders.

Many people have made and lost money in equal measures. In fact, I recently heard a story of a 45 year old banker who resigned from a top job to day trade. He ran out of cash a few days after starting out. Similar stories have been told a lot in the past.

Therefore, for you as a trader, it is very important to remain vigilant and to use viable strategies to avoid making these losses. There are hundreds of strategies out there. These strategies have been tested and proven for a very long time. Therefore, as a trader, the idea is to find a few strategies and use them in different types of markets. In this article, I will introduce you to algorithmic trading and highlight a few details about how to develop your own trading strategy.

What is algorithmic trading?

Algorithmic trading is a concept where you use different codes to align your technical indicators to that. In the past, algorithmic trading was a preserve of people with a lot of coding experience and expertise. Today, anyone without all this knowledge is able to develop his algorithms and executing them using a simple drag and drop strategy. Drag and dropping strategy is one where you take previously developed tools and dragging them in order. After you have developed your algorithmic tools, you can deploy them to execute the trades when you are there and when you are not. You can also develop algorithms to automatically alert you once a particular market meets your trading expectations.

See Also: Basics of Algorithmic Trading: Concepts and Examples

Key components of trading algorithms

To develop a good algorithm to trade, a number of items are needed. One, you need indicators. The whole idea is to act when certain criteria of technical indicators are met. There are many technical indicators that you can use. However, I recommend that you combine only a few indicators that you have mastered well in your trading experience. I recommend using the following: Moving Averages, Parabolic SAR, Stichastics, Relative Strength Index, and Relative Vigour Index. By having this set of indicators, you will be at the right direction.

The next component of algorithms is the inputs. These inputs are usually assigned to the other nodes to create an algorithm. There are usually four types of inputs available which include: string, integer, Boolean, and number.

Next, we have the variables. There are usually various corresponding variables for each data type. These data types are: Boolean, number, text, and date time. These variables will tell the algorithm what to do and when.

The next important aspects are mathematical features which include: +, -, and = among others.

Last but not least, the logic are very important. They include: And, and Or. For instance, you can direct the algorithm to open a buy trade when the RSI value is 29 and the Stochastics is at 28. Here, you can use both.

Backtesting

One of the most important aspect of developing algo tools is setting the duration. For a day trader, it would be erroneous to use long-term values such as a 200 day moving average. The fact is that it won’t tell you the right thing. Therefore, you should use short term durations in developing your programs.

After you have developed your Expert Advisor (another term for algotithms), the most important thing you should do is backtesting it. If you have not done this, you can be certain that you won’t succeed. Backtesting gives you a chance to take your algo back in time and see how well it has performed. If you find that it has not done well, chances are that it won’t do that well in future. So, you should avoid it. Alternatively, you can recreate and backtest it until it works properly.

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